Graduation Year

2008

Document Type

Dissertation

Degree

Ph.D.

Degree Granting Department

Electrical Engineering

Major Professor

Elias. K. Stefanakos, Ph.D.

Co-Major Professor

Kimon P. Valavanis, Ph.D.

Keywords

Gimball platform, Lithium batteries, Lead acid batteries, Fuel cells, Super-capacitors

Abstract

Unmanned ground and aerial vehicles (UGVs and UAVs) have strict payload limitations, limited free space affecting on board power availability resulting in limited endurance and operational range. This limitation is exacerbated by the addition of sensors, actuators and other related equipment needed to accomplish mission objectives in diverse applications. Two energy sources are mainly available for mobile applications; batteries and fuel cells. Batteries are a relatively cheap, tested technology with good performance under varying loads. On the other hand, fuel cells offer fast and easy refueling solutions. Furthermore, preliminary studies have shown that a hybrid system can combine the advantages of both technologies offering a superior system. It is true that for most outdoors applications, payload needs, sensor suite utilization and energy requirements are apriori unpredictable.

This makes proper sizing of energy storage devices and the prediction of remaining available energy rather difficult tasks. This research proposes an indirect way of improving the operational range for UAVs of Vertical Take Off and Landing (VTOLs), since the VTOL vehicle is transported to the mission site without the need to fly. The proposed gimballed platform, which will be a power source itself, rotates around two axes perpendicular to each other, allowing the VTOL to take-off and land, regardless of the position of the UGV, while securing it during transportation. The UGV can also serve as a charging station for the VTOL. Furthermore, this research proposes a Matlab Simulation tool that can simulate the energy and power demand of small to mid-sized robotic vehicles. This model will simulate the power consumption in the motors based on Skid steering, road gradient, linear and angular velocity.

With the energy and power requirements estimated, a Matlab optimization tool is proposed to be used to determine the optimal configuration of a power system for mobile applications under constraints relating to capacity/runtime, weight, volume, cost, and system complexity. The configuration will be based on commercially available batteries, and fuel cells to significantly reduce cost and delivery time. The optimization tool can be used for any mobile application. Finally, a new model is proposed for the accurate prediction of battery runtime and remaining energy for single battery discharge. This model reformulates Peukert's equation and achieves higher accuracy by introducing a new concept of variable exponent which is a function of battery capacity and discharge current.

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